R version 4.0.2 (2020-06-22)
Platform: x86_64-apple-darwin17.0 (64-bit)
locale: en_US.UTF-8||en_US.UTF-8||en_US.UTF-8||C||en_US.UTF-8||en_US.UTF-8
attached base packages: stats, graphics, grDevices, utils, datasets, methods and base
other attached packages: pander(v.0.6.3), cbmbtools(v.0.0.0.9034), vegan(v.2.5-6), lattice(v.0.20-41), permute(v.0.9-5), ggpubr(v.0.4.0), knitr(v.1.29), scales(v.1.1.1), gtools(v.3.8.2), tidyselect(v.1.1.0), forcats(v.0.5.0), stringr(v.1.4.0), dplyr(v.1.0.1), purrr(v.0.3.4), readr(v.1.3.1), tidyr(v.1.1.1), tibble(v.3.0.3), ggplot2(v.3.3.2) and tidyverse(v.1.3.0)
loaded via a namespace (and not attached): httr(v.1.4.2), jsonlite(v.1.7.0), splines(v.4.0.2), carData(v.3.0-4), modelr(v.0.1.8), assertthat(v.0.2.1), blob(v.1.2.1), cellranger(v.1.1.0), yaml(v.2.2.1), pillar(v.1.4.6), backports(v.1.1.8), glue(v.1.4.1), digest(v.0.6.25), ggsignif(v.0.6.0), rvest(v.0.3.6), colorspace(v.1.4-1), Matrix(v.1.2-18), htmltools(v.0.5.0), pkgconfig(v.2.0.3), broom(v.0.7.0), haven(v.2.3.1), openxlsx(v.4.1.5), rio(v.0.5.16), mgcv(v.1.8-31), generics(v.0.0.2), car(v.3.0-9), ellipsis(v.0.3.1), withr(v.2.2.0), cli(v.2.0.2), magrittr(v.1.5), crayon(v.1.3.4), readxl(v.1.3.1), evaluate(v.0.14), fs(v.1.5.0), fansi(v.0.4.1), nlme(v.3.1-148), MASS(v.7.3-51.6), rstatix(v.0.6.0), xml2(v.1.3.2), foreign(v.0.8-80), tools(v.4.0.2), data.table(v.1.13.0), hms(v.0.5.3), lifecycle(v.0.2.0), munsell(v.0.5.0), reprex(v.0.3.0), cluster(v.2.1.0), zip(v.2.0.4), compiler(v.4.0.2), rlang(v.0.4.7), grid(v.4.0.2), rstudioapi(v.0.11), rmarkdown(v.2.3), codetools(v.0.2-16), gtable(v.0.3.0), abind(v.1.4-5), DBI(v.1.1.0), curl(v.4.3), R6(v.2.4.1), lubridate(v.1.7.9), stringi(v.1.4.6), parallel(v.4.0.2), Rcpp(v.1.0.5), vctrs(v.0.3.2), dbplyr(v.1.4.4) and xfun(v.0.16)
Kruskal-Wallis rank sum test
data: Gene_16S_copies_per_mL by Sample_Type
Kruskal-Wallis chi-squared = 29.276, df = 6, p-value = 5.394e-05
Pairwise comparisons using Wilcoxon rank sum exact test
data: ddpcr$Gene_16S_copies_per_mL and ddpcr$Sample_Type
NTC Iso_Ctrl PBS Syringe_Rinse Homog_Ctrl BAL
Iso_Ctrl 0.64000 - - - - -
PBS 0.58947 0.40000 - - - -
Syringe_Rinse 0.42353 0.03333 0.40000 - - -
Homog_Ctrl 0.58947 0.16667 0.42353 0.40000 - -
BAL 0.22238 0.00839 0.31818 0.27082 0.90909 -
Lung 0.00839 0.00262 0.07955 0.00839 0.07955 0.00023
P value adjustment method: BH
Call:
adonis(formula = adonis.hel.df.wbn ~ otu.df.lungsamp.sampctrls$RA_Groups, permutations = 10000, method = "euclidean")
Permutation: free
Number of permutations: 10000
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2
otu.df.lungsamp.sampctrls$RA_Groups 2 3.8879 1.94394 2.3806 0.16554
Residuals 24 19.5980 0.81658 0.83446
Total 26 23.4859 1.00000
Pr(>F)
otu.df.lungsamp.sampctrls$RA_Groups 9.999e-05 ***
Residuals
Total
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Call:
adonis(formula = adonis.hel.bl ~ adonis.otudf.bl$Sample_Type, permutations = 10000, method = "euclidean")
Permutation: free
Number of permutations: 10000
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
adonis.otudf.bl$Sample_Type 1 2.4484 2.4484 3.1334 0.15563 9.999e-05 ***
Residuals 17 13.2838 0.7814 0.84437
Total 18 15.7323 1.00000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Call:
adonis(formula = adonis.hel.wn ~ adonis.otudf.wn$RA_Groups, permutations = 10000, method = "euclidean")
Permutation: free
Number of permutations: 10000
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
adonis.otudf.wn$RA_Groups 1 2.4698 2.46976 3.3064 0.18061 4e-04 ***
Residuals 15 11.2046 0.74697 0.81939
Total 16 13.6744 1.00000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Call:
adonis(formula = adonis.hel.bn ~ adonis.otudf.bn$Organ, permutations = 10000, method = "euclidean")
Permutation: free
Number of permutations: 10000
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
adonis.otudf.bn$Organ 1 0.9148 0.91483 0.99522 0.05856 0.463
Residuals 16 14.7076 0.91922 0.94144
Total 17 15.6224 1.00000
Call:
adonis(formula = otu.good.lungsamp.isoctrls_hel ~ otu.df.lungsamp.isoctrls$Sample_Type, permutations = 10000, method = "euclidean")
Permutation: free
Number of permutations: 10000
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2
otu.df.lungsamp.isoctrls$Sample_Type 3 5.0693 1.6898 2.0376 0.1846
Residuals 27 22.3910 0.8293 0.8154
Total 30 27.4603 1.0000
Pr(>F)
otu.df.lungsamp.isoctrls$Sample_Type 9.999e-05 ***
Residuals
Total
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Call:
adonis(formula = adonis.hel.il ~ adonis.otudf.il$RA_Groups, permutations = 10000, method = "euclidean")
Permutation: free
Number of permutations: 10000
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
adonis.otudf.il$RA_Groups 1 2.6804 2.68040 3.4196 0.15253 9.999e-05 ***
Residuals 19 14.8927 0.78383 0.84747
Total 20 17.5731 1.00000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Call:
adonis(formula = adonis.hel.ib ~ adonis.otudf.ib$RA_Groups, permutations = 10000, method = "euclidean")
Permutation: free
Number of permutations: 10000
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
adonis.otudf.ib$RA_Groups 1 1.2087 1.20866 1.3141 0.06165 0.07309 .
Residuals 20 18.3957 0.91978 0.93835
Total 21 19.6044 1.00000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Call:
adonis(formula = otu.good.lungsamp.seqctrls_hel ~ otu.df.lungsamp.seqctrls$Sample_Type, permutations = 10000, method = "euclidean")
Permutation: free
Number of permutations: 10000
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2
otu.df.lungsamp.seqctrls$Sample_Type 3 7.919 2.63959 3.2847 0.16193
Residuals 51 40.984 0.80361 0.83807
Total 54 48.903 1.00000
Pr(>F)
otu.df.lungsamp.seqctrls$Sample_Type 9.999e-05 ***
Residuals
Total
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Call:
adonis(formula = adonis.hel.sl ~ adonis.otudf.sl$RA_Groups, permutations = 10000, method = "euclidean")
Permutation: free
Number of permutations: 10000
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
adonis.otudf.sl$RA_Groups 1 4.146 4.1459 5.1613 0.10717 9.999e-05 ***
Residuals 43 34.541 0.8033 0.89283
Total 44 38.687 1.00000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Call:
adonis(formula = adonis.hel.sb ~ adonis.otudf.sb$RA_Groups, permutations = 10000, method = "euclidean")
Permutation: free
Number of permutations: 10000
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
adonis.otudf.sb$RA_Groups 1 2.069 2.06931 2.3933 0.05159 5e-04 ***
Residuals 44 38.044 0.86463 0.94841
Total 45 40.113 1.00000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Call:
adonis(formula = otu.good.tong.lungsamp_hel ~ otu.df.tong.lungsamp$Sample_Type, permutations = 10000, method = "euclidean")
Permutation: free
Number of permutations: 10000
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
otu.df.tong.lungsamp$Sample_Type 2 3.9663 1.98317 2.6355 0.12772 9.999e-05
Residuals 36 27.0894 0.75248 0.87228
Total 38 31.0557 1.00000
otu.df.tong.lungsamp$Sample_Type ***
Residuals
Total
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Call:
adonis(formula = adonis.hel.tl ~ adonis.otudf.tl$Sample_Type, permutations = 10000, method = "euclidean")
Permutation: free
Number of permutations: 10000
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
adonis.otudf.tl$Sample_Type 1 1.039 1.03903 1.5005 0.05265 0.0119 *
Residuals 27 18.696 0.69244 0.94735
Total 28 19.735 1.00000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Call:
adonis(formula = adonis.hel.tb ~ adonis.otudf.tb$Sample_Type, permutations = 10000, method = "euclidean")
Permutation: free
Number of permutations: 10000
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
adonis.otudf.tb$Sample_Type 1 2.6012 2.60116 3.2809 0.10489 9.999e-05 ***
Residuals 28 22.1989 0.79282 0.89511
Total 29 24.8001 1.00000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = tukey_otu_df[, "Unique_Otus_per_1k_reads"] ~ tukey_otu_df[, "Alpha_Div_Groups"])
$`tukey_otu_df[, "Alpha_Div_Groups"]`
diff lwr upr
Isolation Control-BAL -10.612291 -27.006526 5.7819429
Lung-BAL 25.049970 7.457534 42.6424053
Sampling Control-BAL -2.528455 -20.690372 15.6334619
Sequencing Control-BAL -13.515401 -27.202081 0.1712778
Lung-Isolation Control 35.662261 18.778539 52.5459833
Sampling Control-Isolation Control 8.083837 -9.392476 25.5601491
Sequencing Control-Isolation Control -2.903110 -15.666004 9.8597843
Sampling Control-Lung -27.578425 -46.183380 -8.9734692
Sequencing Control-Lung -38.565371 -52.834721 -24.2960216
Sequencing Control-Sampling Control -10.986946 -25.952766 3.9788736
p adj
Isolation Control-BAL 0.3746804
Lung-BAL 0.0014826
Sampling Control-BAL 0.9950044
Sequencing Control-BAL 0.0545862
Lung-Isolation Control 0.0000011
Sampling Control-Isolation Control 0.6949822
Sequencing Control-Isolation Control 0.9684857
Sampling Control-Lung 0.0008519
Sequencing Control-Lung 0.0000000
Sequencing Control-Sampling Control 0.2510366
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = tukey_otu_df[, "Shannon"] ~ tukey_otu_df[, "Alpha_Div_Groups"])
$`tukey_otu_df[, "Alpha_Div_Groups"]`
diff lwr upr p adj
Isolation Control-BAL -0.9947478 -1.8514868 -0.1380087 0.0147639
Lung-BAL 0.6346623 -0.2846930 1.5540176 0.3098538
Sampling Control-BAL -0.5859416 -1.5350572 0.3631740 0.4234102
Sequencing Control-BAL -1.2226705 -1.9379166 -0.5074244 0.0000876
Lung-Isolation Control 1.6294101 0.7470911 2.5117290 0.0000205
Sampling Control-Isolation Control 0.4088062 -0.5044807 1.3220931 0.7201786
Sequencing Control-Isolation Control -0.2279227 -0.8948932 0.4390477 0.8732743
Sampling Control-Lung -1.2206039 -2.1928720 -0.2483357 0.0067338
Sequencing Control-Lung -1.8573328 -2.6030284 -1.1116372 0.0000000
Sequencing Control-Sampling Control -0.6367289 -1.4188211 0.1453633 0.1637833
[1] 87 2
Pairwise comparisons using Wilcoxon rank sum test with continuity correction
data: bray_dist_lbtce_long_mut_filt_uniq$BC_Index and bray_dist_lbtce_long_mut_filt_uniq$Sample_Type
BAL Blank Cecum Lung
Blank 0.2730 - - -
Cecum < 2e-16 < 2e-16 - -
Lung 6.3e-09 7.4e-06 < 2e-16 -
Tongue < 2e-16 8.5e-13 < 2e-16 0.0053
P value adjustment method: BH
Wilcoxon rank sum exact test
data: BC_Index by Comparison_Type
W = 85, p-value = 0.0004114
alternative hypothesis: true location shift is not equal to 0